Data / Context Engineer

Glint Tech Solutions • Texas, TX

4d • Remote

About The Position

A leading enterprise client, a multinational telecommunications technology company, is seeking a Data / Context Engineer to play a pivotal role in shaping how knowledge flows across a massive, multi-region operation. This is a high-visibility opportunity to architect and scale a knowledge base (KB) system that will directly power decision-making across 12 regions and beyond. The role sits at the intersection of AI infrastructure, data engineering, and real-world business impact, with contributions visible across a nationwide operation from day one.

Requirements

• 4-6 years of hands-on RAG / retrieval / vector store engineering in production
• Experience building a multi-tenant or multi-region retrieval architecture with overlay / inheritance semantics, not just "one big index"
• Vertex AI Vector Search or transferable depth (Pinecone, Weaviate, pgvector with strong tenancy, OpenSearch hybrid)
• Embedding model evaluation discipline — retrieval quality metrics (recall@k, precision@k, MRR), not vibes
• Python; familiar with structured-doc ingestion pipelines (PDF / XML / spreadsheet chunked, normalized, embedded)

Nice To Haves

• Designed a promotion path between draft/approved/retired patterns with audit log
• Sampled human-review workflows integrated with the writeback path
• RF / telecom standards format familiarity

Responsibilities

• Sign and implement the multi-regional KB architecture in P1 alongside SA
• Seed the KB across 12 regions during P2 (cohort 1 wk1, cohort 2 wk2, cohort 3 wk3 of July)
• Build and operate the ingestion pipeline (machine-readable regional standards embeddings retrievable patterns) with sampled human approval gate
• Add MOD-specific retrievable context as regional overlays during Sep-Oct
• Own KB integrity checks, retrieval evaluation, and weekly health reporting

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed